Greetings!
Zoho introduced significant updates to Zoho CRM’s scoring capabilities, enhancing the existing Multiple Scoring Rules (MSR) with powerful new additions—including Zia Scores. These improvements allow deeper behavioral analysis through AI-powered scoring elements, covering multiple communication channels and customer signals.
With this release, Zia Scores are now integrated with manual scoring rules, enabling businesses to trigger automation workflows based on enriched, AI-analyzed data across all CRM modules.
What’s New?
Under Automation > Scoring Rules, you’ll now see Manual Scoring and Zia Scoring options available side-by-side, offering a unified setup for all your scoring logic.
Manual Scores: What’s Enhanced?
Manual scoring allows organizations to evaluate leads or customers based on behavioral patterns, demographics, communication history, and more.
The latest enhancements expand the scope of manual scoring rules by:
Adding Voice of Customer (VoC) Insights as a scoring channel.
Incorporating AI-powered factors like sentiment, intent, emotion, and keyword mentions.
Supporting new time-based and value-based operators (e.g., “Call made in the last 20 days”).
Merging Email and Email Insights into a single streamlined channel.
You can define rules only for the features and integrations currently active in your CRM setup.
Zia Scores now include a variety of scoring types, such as health scores, engagement scores, follow-up scores, field attribute scores, and conversion scores. This flexibility enables businesses to tailor the scoring mechanisms to align with their processes better, enhancing decision-making and outcome prediction.

This feature extends the power of Zia's AI-driven insights across all modules and improves Zoho CRM's adaptability to diverse business needs.
Manual Scores
Let's look at the enhancements to manual scores in detail:
The MSR feature now includes VoC Insights as a separate channel, which provides users with a deeper understanding of each record's interactions by setting conditions and points based on VoC.

To a few channels—like surveys, emails, help desk, phone, and social media—Zoho have added AI factors like sentiments, emotions, intents, and insights, all captured through VoC. This overcomes the previous limitation of traditional CRM metrics lacking VoC data.

Scoring rules provide additional operator options, such as setting criteria for specific time frames, checking number values, and more. For instance, you can add 10 points specifically for those who attended calls in the last 20 days.

Operators determine how rules should operate for the points being added or subtracted.
Zoho've combined factors listed under Email and Email Insights into one channel—Email—to avoid confusion.
Please refer to the table below for the consolidated list of the new factors against their respective channels:
Channel | New Factors |
Business message | Incoming message |
Sales IQ | Each SalesIQ chat missed |
Calls | Each call made Call attended Call unattended Call received Call missed | Call duration Call sentiment Call intent Call emotion Call keyword |
Desk | New ticket New rating Ticket escalated New comment New response | Ticket overdue Mention Sentiment Intent Keyword |
Email | Total emails received Competitor mentions Competitor mention count | Keyword Sentiment Intent Emotion |
Survey | Sentiment Intent | Keyword |
VoC Insights | Record sentiment Record intent Record keyword | Competitor mention Competitor mention count Churn out |
Deal Insights (VoC) | Closed won | Closed lost
|
Field Attribute Score
Evaluates data quality, completeness, and relevance in CRM records based on selected fields.
Conversion Score
Calculates the likelihood of converting based on data across related modules (e.g., Leads, Deals).
Engagement Score
Assesses interest levels using interactions from calls, emails, meetings, and other communication modules.
Follow-up Score
Measures the effectiveness and timeliness of sales follow-ups.
Health Score
Offers a comprehensive view of the customer relationship by evaluating touchpoints across support, sales, campaigns, and more.
How Zia Learns – Training Data
For Field Attribute and Conversion Scores, you must provide training data—a set of records marked as ideal or non-ideal—which helps Zia learn what success looks like.